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Title:Real-time motor unit identification from high-density surface EMG
Authors:ID Glaser, Vojko (Author)
ID Holobar, Aleš (Author)
ID Zazula, Damjan (Author)
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Language:English
Work type:Unknown
Typology:1.01 - Original Scientific Article
Organization:UNG - University of Nova Gorica
Abstract:This study addresses online decomposition of high-density surface electromyograms (EMG) in real-time. The proposed method is based on previouslypublished Convolution Kernel Compensation (CKC) technique and sharesthe same decomposition paradigm, i.e. compensation of motor unit action potentials and direct identification of motor unit (MU) discharges. In contrast to previously published version of CKC, which operates in batch mode and requires ~ 10 s of EMG signal, the real-time implementation begins with batch processing of ~ 3 s of the EMG signal in the initialization stage and continues on with iterative updating of the estimators of MU discharges as blocks of new EMG samples become available. Its detailed comparison to previously validated batch version of CKC and asymptotically Bayesian optimal Linear Minimum Mean Square Error (LMMSE) estimator demonstrates high agreementin identified MU discharges among all three techniques. In the case of synthetic surface EMG with 20 dB signal-to-noise ratio, MU discharges were identified with average sensitivity of 98 %. In the case of experimental EMG, real-time CKC fully converged after initial 5 s of EMG recordings and real-time and batch CKC agreed on 90 % of MU discharges, on average. The real-time CKC identified slightly fewer MUs than its batch version (experimental EMG, 4 MUs versus 5 MUs identified by batch CKC, on average), but required only 0.6 s of processing time on regular personal computer for each second of multichannel surface EMG.
Keywords:discharge pattern, high-density EMG, surface EMG, motor unit, real time decomposition
Year of publishing:2013
Number of pages:str. 949-958
Numbering:Vol. 21, no. 6
PID:20.500.12556/RUNG-2059 New window
COBISS.SI-ID:17016854 New window
UDC:007.5:61
ISSN on article:1534-4320
DOI:10.1109/TNSRE.2013.2247631 New window
NUK URN:URN:SI:UNG:REP:Z3DQEIWU
Publication date in RUNG:05.01.2016
Views:6548
Downloads:0
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GLASER, Vojko, HOLOBAR, Aleš and ZAZULA, Damjan, 2013, Real-time motor unit identification from high-density surface EMG. IEEE transactions on neural systems and rehabilitation engineering [online]. 2013. Vol. 21, no. 6, p. 949–958. [Accessed 16 April 2025]. DOI 10.1109/TNSRE.2013.2247631. Retrieved from: https://repozitorij.ung.si/IzpisGradiva.php?lang=eng&id=2059
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Record is a part of a journal

Title:IEEE transactions on neural systems and rehabilitation engineering
Shortened title:IEEE trans. neural syst. rehabil. eng.
Publisher:IEEE
ISSN:1534-4320
COBISS.SI-ID:320873 New window

Document is financed by a project

Funder:EC - European Commission
Funding programme:FP7
Project number:287739
Name:A novel concept for support to diagnosis and remote management of tremor
Acronym:NeuroTREMOR

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